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A Building Classification System for Multi-hazard Risk Assessment

International Journal of Disaster Risk Science 2022年第2期13卷 161-177页

作者： Vitor Silva Svetlana Brzev Charles Scawthorn Catalina Yepes Jamal Dabbeek helen crowley Risk Section Global Earthquake Model27100 PaviaItaly Department of Civil Engineering University of British ColumbiaVancouverBC V6T 1Z4Canada SPA Risk LLC DenverCO 80207USA Department of Civil Engineering An-Najah National UniversityNablusState of Palestine Seismic Risk Section 27100 EucentrePaviaItaly

A uniform and comprehensive classification system, often referred to as taxonomy, is fundamental for the characterization of building portfolios for natural hazard risk assessment. A building taxonomy characterizes assets according to attributes that can influence the likelihood of damage due to the effects of natural *** the scope of the Global Earthquake Model(GEM)initiative, a building taxonomy(GEM Building Taxonomy V2.0) was developed with the goal of classifying buildings according to their seismic vulnerability. This taxonomy contained 13 building attributes, including the main material of construction, lateral load-resisting system, date of construction and number of stories. Since its release in2012, the taxonomy has been used by hundreds of experts working on exposure and risk modeling efforts. These applications allowed the identification of several limitations, which led to the improvement and expansion of this taxonomy into a new classification system compatible with multi-hazard risk assessment. This expanded taxonomy(named GED4ALL) includes more attributes and several details relevant for buildings exposed to natural hazards beyond earthquakes. GED4ALL has been applied in several international initiatives, enabling the identification of the most common building classes in the world, and facilitating compatibility between exposure models and databases of vulnerability and damage databases.

关键词： Disaster risk Exposure Multihazard Taxonomy

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ShakeDaDO:A data collection combining earthquake building damage and ShakeMap parameters for Italy

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Artificial Intelligence in Geosciences 2020年第1期1卷 36-51页

作者： Licia Faenza Alberto Michelini helen crowley Barbara Borzi Marta Faravelli INGV Istituto Nazionale di Geofisica e VulcanologiaItaly EUCENTRE Centro Europeo di Formazione e Ricerca in Ingegneria SismicaItaly

In this article,we present a new data collection that combines information about earthquake damage with seismic *** from the ***,which provides information on the damage of individual buildings subjected to sequences of past earthquakes in Italy,we have generated ShakeMaps for all the events with magnitude greater than 5.0 that have contributed to these *** sequences under examination are those of Irpinia 1980,Umbria Marche 1997,Pollino 1998,Molise 2002,L’Aquila 2009 and Emilia *** this way,we were able to combine,for a total of the 117,695 buildings,the engineering parameters included in Da.D.O.,but revised and reprocessed in this application,and the ground shaking data for six different variables(namely,intensity in MCS scale,PGA,PGV,SA at 0.3s,1.0s and 3.0s).The potential applications of this data collection are innumerable:from recalibrating fragility curves to training machine learning models to quantifying earthquake *** data collection will be made available within Da.D.O.,a platform of the Italian Department of Civil Protection,developed by EUCENTRE.

关键词： ShakeMap Building damage Italian earthquakes Data collection

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